US 12,321,700 B2
Methods, systems, and media for bi-modal generation of natural languages and neural architectures
Mohammad Akbari, Coquitlam (CA); Amin Banitalebi Dehkordi, Vancouver (CA); Behnam Kamranian, North Vancouver (CA); and Yong Zhang, Richmond (CA)
Assigned to HUAWEI CLOUD COMPUTING TECHNOLOGIES CO., LTD., Gui'An New District (CN)
Filed by Mohammad Akbari, Coquitlam (CA); Amin Banitalebi Dehkordi, Vancouver (CA); Behnam Kamranian, North Vancouver (CA); and Yong Zhang, Richmond (CA)
Filed on Jul. 29, 2022, as Appl. No. 17/877,705.
Prior Publication US 2024/0037335 A1, Feb. 1, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 40/284 (2020.01); G06N 3/045 (2023.01)
CPC G06F 40/284 (2020.01) [G06N 3/045 (2023.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
obtaining a generative bi-modal model trained with a bi-modal understanding of natural language in relation to neural network architectures;
providing input information to the model, the input information comprising at least one of the following:
natural language information; and
neural network architecture information; and
using the model to:
encode the input information to generate encoded representations of the input information; and
decode the encoded representations of the input information to generate output information comprising at least one of:
natural language information; and
neural network architecture information,
wherein the input information comprises:
natural language information comprising a question; and
neural network architecture information corresponding to a first neural network architecture; and
wherein the output information comprises natural language information comprising an answer responsive to the question with respect to the first neural network architecture.